This paper presents an adaptive interference-aware receiver for multiuser multiple-input multiple-output (MU-MIMO) downlink systems in wireless local area network (WLAN) systems. The MU-MIMO downlink technique is one of the key techniques that are newly applied to WLAN systems in order to support a very high throughput. However, the simultaneous communication of several users causes inter-user interference (IUI), which adversely affects receivers. Therefore, in order to prevent IUI, a precoding technique is defined at the transmitter based on feedback from the receiver. Unfortunately, however, the receiver still suffers from interference, because the precoding technique is prone to practical errors from the feedback quantization and subcarrier grouping scheme. Whereas ordinary detection schemes are available to mitigate such interference, such schemes are unsuitable because of their low performance or high computational complexity. In this paper, we propose an switching algorithm based on the norm ratio between an effective channel matrix for the desired signal and that of the interfering signals. Simulation results based on the IEEE 802.11ac standard show that the proposed algorithm can achieve near-optimal performance with a 70% reduction in computational complexity.

Since many cyber-physical systems (CPSs) manipulate security-sensitive data, enhancing the quality of security in a CPS is a critical and challenging issue in CPS design. Although there has been a large body of research on securing general purpose PCs, directly applying such techniques to a CPS can compromise the real-time property of CPSs since the timely execution of tasks in a CPS typically relies on real-time scheduling. Recognizing this property, previous works have proposed approaches to add a security constraint to the real-time properties to cope with the information leakage problem that can arise between real-time tasks with different security levels. However, conventional works have mainly focused on non-preemptive scheduling and have suggested a very naive approach for preemptive scheduling, which shows limited analytical capability. In this paper, we present a new preemptive fixed-priority scheduling algorithm incorporating a security constraint, called lowest security-level first (LSF) and its strong schedulability analysis to reduce the potential of information leakage. Our simulation results show that LSF schedulability analysis outperforms state-of-the-art FP analysis when the security constraint has reasonable timing penalties.

In heterogeneous networks, network selection is an important task for reconfigurable mobile devices (MDs). In the reconfigurable MD architecture that has been standardized by the European Telecommunications Standards Institute (ETSI), the network selection functionality is handled by a software component called Mobility Policy Manager (MPM). In this paper, we present an implementation of the MPM whereby a reconfigurable MD conforming to the ETSI standard can select the most appropriate radio access network (RAN) to use. We implemented a reconfigurable MD test-bed compliant with the ETSI standard, and show that the network selection driven by the MPM enhances the throughput of the receiving MD by about 26% compared to the arbitrary network selection provided by a conventional reconfigurable MD without the functionality of MPM, verifying the functionality of the MPM.

We propose a simple configuration for colorless and directionless (CD) reconfigurable optical add/drop multiplexers that enables ultra-low contention add/drop operation to be achieved. In the configuration, we apply a combination of multiple small-port-count CD add/drop banks (CD banks) and round-robin CD bank assignment. Evaluation results show that the proposed configuration can substantially reduce intra-node contention rate, which is less than 0.1%. We also find that the proposed configuration can improve the utilization efficiency of wavelength resources and transponders. We discuss the mechanism of how the proposed configuration reduces intra-node contention by analyzing the status of wavelength assignments in direction ports and CD banks.

We arrange disaster mitigation activities into temporal order and discuss the contribution of information and communications technology (ICT) to the reduction of disaster damage in the stages of precaution, emergency response, and post-mortem study. Examples of the current contribution of ICT are introduced and future possible uses of ICT are discussed. We focus on the contribution of ICT to decision-making in emergency responses by augmenting human intelligence. Research directions of ICT for disaster mitigation technology are summarized in the categories “tough ICT”, “intelligence amplification for decision-making in disaster mitigation” and “safe ICT.”

The purpose of this paper is to show that a new type of information-theoretic learning method called “potential learning” can be used to detect and extract important tweets among a great number of redundant ones. In the experiment, we used a dataset of 10,000 tweets, among which there existed only a few important ones. The experimental results showed that the new method improved overall classification accuracy by correctly identifying the important tweets.

As the demand for higher transmission rates and spectral efficiency is steadily increasing, the research and development of novel mobile communication systems has gained momentum. This paper focuses on providing a comprehensive survey of research and development activities on fifth generation mobile communication systems in Japan. We try to survey a vast area of wireless communication systems and the developments that led to future 5G systems.

Recently, multihop wireless sensor networks (WSNs) are widely developed and applied to energy efficient data collections from environments by establishing reliable transmission radio links and employing data aggregation algorithms, which can eliminate redundant transmissions and provide fusion information. In this paper, energy efficiency which consists of not only energy consumptions but also the amount of received data by the base station, as the performance metric to evaluate network utilities is presented for achieving energy efficient data collections. In order to optimize energy efficiency for improvements of network utilization, we firstly establish a graphical game theoretic model for energy efficiency in multihop WSNs, considering message length, practical energy consumptions and packet success probabilities. Afterwards, we propose a graphical protocol for performance optimization from Nash equilibrium of the graphical game theory. The approach also consists of the distributed protocol for generating optimum tree networks in practical WSNs. The experimental results show energy efficient multihop communications can be achieved by optimum tree networks of the approach. The quantitative evaluation and comparisons with related work are presented for the metric with respect to network energy consumptions and the amount of received data by the base station. The performances of our proposal are improved in all experiments. As an example, our proposal can achieve up to about 52% energy efficiency more than collection tree protocol (CTP). The corresponding tree structure is provided for the experiment.

A link adaptation scheme is devised for vector-perturbation (VP) zero-forcing beamforming (ZFBF) MIMO precoding and a link-adaptable VP-ZFBF precoder is applied to multi-point three-dimensional (3D) beamformers to be used in mmWave-band wireless access systems. Channel coding schemes used in current systems, e.g., turbo codes, possess systematic code structures. The VP gain can thus be predicted by searching for perturbation vectors for the symbol vectors mapped from information bits. On the basis of this principle, we constructed an efficient iterative modulation-and-coding-set (MCS) selection procedure for VP-ZFBF precoding. Simulation results demonstrate that our proposed scheme suitably passed on the VP gain to the selection of an appropriate higher-rate MCS index and thus achieved high throughputs by incorporating with multi-point 3D-beamformers.

A demonstration of power enhancement by nonlinear oscillation in a millimeter-sized electrostatic vibrational energy harvester for the future Internet of Things is presented. To enable nonlinearity in microelectromechanical system (MEMS) devices, we selected a gold spring as a component of the MEMS structure for its lower Young's modulus than conventional materials, a ductile characteristic, and an electrical conductivity. The mechanical characteristics of the fabricated MEMS device related to the nonlinear phenomenon were examined. The charging characteristics of an ethylene tetrafluoroethylene copolymer (ETFE) electret film for electrostatic induction were also evaluated. Nonlinear oscillation for the millimeter-sized energy harvester with the ETFE electret was confirmed experimentally by applying external vibration. The oscillation resulted in a bandwidth two times broader than that by linear oscillation. The normalized harvester effectiveness of the nonlinear oscillation was 5.1 times higher than that of the linear one.

A novel optical high order quadrature amplitude modulation (QAM) transmission system for high-speed short links is described. Dual-polarization (DP) QAM and twin local lights are generated from one light source in the system, and these lightwaves are simultaneously transmitted via standard single mode fiber. The receiver can be constructed simply because it does not require a coherent light source under wavelength control. The system enables a 3.1 Gbaud DP-16-QAM signal to be successfully demodulated after 80-km transmission without using an optical dispersion compensator. It also achieves high tolerance against phase noise in the signal light source.

Interference alignment (IA) is a method to improve the capacity of cell-edge users and thus attracts an intense research interest. We focus on the IA extended to the multiple-input multiple-output (MIMO) interference network. In this method, each coordinated transmitter generates beamforming vectors to align interference from different transmitters into confined subspace at each receiver. Then, using singular value decomposition (SVD) with the relative magnitude coefficients, transmitters calculate the beamforming vectors and the received vectors. However, in this method it is difficult to determine the value of the relative magnitude coefficients so that the system capacity is improved, because it is necessary to solve the non-linear function of multivariable. In this paper, we propose a design method of the relative magnitude coefficients of interference channels to improve system capacity using Brent's method on the K-User MIMO interference channel (MIMO-IFC). The proposed method can improve system capacity, though the system complexity increases due to Brent's method that requires multiple SVD calculation to calculate the null space. Thus, instead of using SVD, we introduce the complexity reduction method to calculate the null space of the matrix. Furthermore, we extend the proposed method to be applicable for more common systems where all base stations have the same number of transmit antennas. Through simulation, we show that the proposed method achieves a higher system capacity than the conventional one. We also show that the method that calculates the null space needs much lower complexity than SVD. In addition, we show that the proposed design method reduces the degradation of the system capacity caused by the interference not eliminated, and achieves the fairness of capacities among users for an increase of the number of design coefficients.

The goal of software testing should go beyond simply finding defects. Ultimately, testing should be focused on increasing customer satisfaction. Defects that are detected in areas of the software that the customers are especially interested in can cause more customer dissatisfaction. If these defects accumulate, they can cause the software to be shunned in the marketplace. Therefore, it is important to focus on reducing defects in areas that customers consider valuable. This article proposes a value-driven V-model (V2 model) that deals with customer values and reflects them in the test design for increasing customer satisfaction and raising test efficiency.

In most existing centralized lighting control systems, the lighting control problem (LCP) is reformulated as a constrained minimization problem and solved by linear programming (LP). However, in real-world applications, LCP is actually discrete and non-linear, which means that more accurate algorithm may be applied to achieve improvements in energy saving. In this paper, particle swarm optimization (PSO) is successfully applied for office lighting control and a linear programming guided particle swarm optimization (LPPSO) algorithm is developed to achieve considerable energy saving while satisfying users' lighting preference. Simulations in DIALux office models (one with small number of lamps and one with large number of lamps) are made and analyzed using the proposed control algorithms. Comparison with other widely used methods including LP shows that LPPSO can always achieve higher energy saving than other lighting control methods.

The reputation-based majority-voting approach is a promising solution for detecting malicious workers in a cloud system. However, this approach has a drawback in that it can detect malicious workers only when the number of colluders make up no more than half of all workers. In this paper, we simulate the behavior of a reputation-based method and mathematically analyze its accuracy. Through the analysis, we observe that, regardless of the number of colluders and their collusion probability, if the reputation value of a group is significantly different from those of other groups, it is a completely honest group. Based on the analysis result, we propose a new method for distinguishing honest workers from colluders even when the colluders make up the majority group. The proposed method constructs groups based on their reputations. A group with the significantly highest or lowest reputation value is considered a completely honest group. Otherwise, honest workers are mixed together with colluders in a group. The proposed method accurately identifies honest workers even in a mixed group by comparing each voting result one by one. The results of a security analysis and an experiment show that our method can identify honest workers much more accurately than a traditional reputation-based approach with little additional computational overhead.

SSDs consist of non-mechanical components (host interface, control core, DRAM, flash memory, etc.) whose integrated behavior is not well-known. This makes an SSD seem like a black-box to users. We analyzed power consumption of four SSDs with standard I/O operations. We find the following: (a) the power consumption of SSDs is not significantly lower than that of HDDs, (b) all SSDs we tested had similar power consumption patterns which, we assume, is a result of their internal parallelism. SSDs have a parallel architecture that connects flash memories by channel or by way. This parallel architecture improves performance of SSDs if the information is known to the file system. This paper proposes three SSD characterization algorithms to infer the characteristics of SSD, such as internal parallelism, I/O unit, and page allocation scheme, by measuring its power consumption with various sized workloads. These algorithms are applied to four real SSDs to find: (i) the internal parallelism to decide whether to perform I/Os in a concurrent or an interleaved manner, (ii) the I/O unit size that determines the maximum size that can be assigned to a flash memory, and (iii) a page allocation method to map the logical address of write operations, which are requested from the host to the physical address of flash memory. We developed a data sampling method to provide consistency in collecting power consumption patterns of each SSD. When we applied three algorithms to four real SSDs, we found flash memory configurations, I/O unit sizes, and page allocation schemes. We show that the performance of SSD can be improved by aligning the record size of file system with I/O unit of SSD, which we found by using our algorithm. We found that Q Pro has I/O unit of 32 KB, and by aligning the file system record size to 32 KB, the performance increased by 201% and energy consumption decreased by 85%, which compared to the record size of 4 KB.

Ternary content addressable memory (TCAM), which can store 0, 1, or X in its cells, is widely used to store routing tables in network routers. Negative bias temperature instability (NBTI) and positive bias temperature instability (PBTI), which increase Vth and degrade transistor switching speed, have become major reliability challenges. This study analyzes the signal probability of routing tables. The results show that many cells retain static stress and suffer significant degradation caused by NBTI and PBTI effects. The bit flipping technique is improved and proactive power gating recovery is proposed to mitigate NBTI and PBTI effects. In order to maintain the functionality of TCAM after bit flipping, a novel TCAM cell design is proposed. Simulation results show that compared to the original architecture, the bit flipping technique improves read static noise margin (SNM) for data and mask cells by 16.84% and 29.94%, respectively, and reduces search time degradation by 12.95%. The power gating technique improves read SNM for data and mask cells by 12.31% and 20.92%, respectively, and reduces search time degradation by 17.57%. When both techniques are used, read SNM for data and mask cells is improved by 17.74% and 30.53%, respectively, and search time degradation is reduced by 21.01%.

The bug reports expressed in natural language text usually suffer from vast, ambiguous and poorly written, which causes the challenge to the duplicate bug reports detection. Current automatic duplicate bug reports detection techniques have mainly focused on textual information and ignored some useful factors. To improve the detection accuracy, in this paper, we propose a new approach calls LNG (LDA and N-gram) model which takes advantages of the topic model LDA and word-based model N-gram. The LNG considers multiple factors, including textual information, semantic correlation, word order, contextual connections, and categorial information, that potentially affect the detection accuracy. Besides, the N-gram adopted in our LNG model is improved by modifying the similarity algorithm. The experiment is conducted under more than 230,000 real bug reports of the Eclipse project. In the evaluation, we propose a new evaluation metric, namely exact-accuracy (EA) rate, which can be used to enhance the understanding of the performance of duplicates detection. The evaluation results show that all the recall rate, precision rate, and EA rate of the proposed method are higher than treating them separately. Also, the recall rate is improved by 2.96%-10.53% compared to the state-of-art approach DBTM.

Visual tracking has been studied for several decades but continues to draw significant attention because of its critical role in many applications. Recent years have seen greater interest in the use of correlation filters in visual tracking systems, owing to their extremely compelling results in different competitions and benchmarks. However, there is still a need to improve the overall tracking capability to counter various tracking issues, including large scale variation, occlusion, and deformation. This paper presents an appealing tracker with robust scale estimation, which can handle the problem of fixed template size in Kernelized Correlation Filter (KCF) tracker with no significant decrease in the speed. We apply the discriminative correlation filter for scale estimation as an independent part after finding the optimal translation based on the KCF tracker. Compared to an exhaustive scale space search scheme, our approach provides improved performance while being computationally efficient. In order to reveal the effectiveness of our approach, we use benchmark sequences annotated with 11 attributes to evaluate how well the tracker handles different attributes. Numerous experiments demonstrate that the proposed algorithm performs favorably against several state-of-the-art algorithms. Appealing results both in accuracy and robustness are also achieved on all 51 benchmark sequences, which proves the efficiency of our tracker.

Fast identification is an urgent demand for modern RFID systems. In this paper, we propose a novel algorithm, access probability adjustment based fine-grained Q-algorithm (APAFQ), to enhance the efficiency of RFID identification with low computation overhead. Specifically, instead of estimation accuracy, the target of most proposed anti-collision algorithms, the APAFQ scheme is driven by updating Q value with two different weights, slot by slot. To achieve higher identification efficiency, the reader adopts fine-grained access probability during the identification process. Moreover, based on the responses from tags, APAFQ adjusts the access probability adaptively. Simulations show the superiority of APAFQ over existing Aloha-based algorithms.